Abstract
Currently, when satellite data volumes grow rapidly and exceed petabyte values and their quality provides reliable analysis of long-term time series, traditional data handling methods assuming local storage and processing may be impossible to implement for small or distributed research teams. Thus, new methods based on modern web technologies providing access to very large distributed data archives are gaining increasing importance. Furthermore, these new data handling solutions should provide not just access but also analysis and processing features, similar to desktop solutions. This paper describes the VEGA-Science web GIS—an open-access novel tool for satellite data processing and analysis. The overview of its architecture and basic technical components is given, but most attention is paid to examples of actual system application for various applied and research tasks. In addition, an overview of projects using the system is given to illustrate its versatility and further development directions are considered.
Highlights
Satellite remote sensing (RS) systems provide regular and long-term observations of vast territories and are increasingly becoming one of the most popular sources of information for studying and monitoring the natural environment
Providing users with a virtual hosting service, letting them create and perform procedures for processing of satellite data provided by the service; Providing users with desktop application replacement tools for analysis of spatial, primarily satellite data, which provide the possibility of distributed work both with data archives of large centers and with computing resources provided by them
The program gateways implemented within the CCU provide full access to data from external sources including Russian satellite systems data from the Roscosmos geoportal archives [39] and Landsat satellites data from Google Cloud
Summary
Satellite remote sensing (RS) systems provide regular and long-term observations of vast territories and are increasingly becoming one of the most popular sources of information for studying and monitoring the natural environment. The increase in the quality of data received from remote sensing systems and the development of processing methods has significantly expanded the field of their application and resulted in the fact that satellite data became practically irreplaceable for solving many scientific and applied tasks. Continuous growth of data volumes from remote sensing satellites and the constantly increasing complexity of data processing methods no longer allow for using traditional approach, which assumes that for each task one had to collect, store, and process data sets on local resources. New approaches are required to enable the use of centralized resources to organize data processing [2,3,4]. The main directions of developments in this case are: Licensee MDPI, Basel, Switzerland
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